Study on Biological Safety of Polyvinyl Alcohol/Collagen Hydrogel as a Tissue Substitute (II)

Physically crosslinked polyvinyl alcohol/collagen composite hydrogels were prepared by a cyclic freezing-drying technique. The biological properties of the hydrogels, including hemolysis, anaphylaxis, pyrogen and acute systemic toxicity tests and implantation in-vivo, were investigated. The hemolysis test suggested that the polyvinyl alcohol/collagen, with a hemolysis index of 1.19%, did not have an obvious hemolysis reaction. There was no toxicosis or death cases observed in the acute systemic toxicity test, and the hydrogel showed no anaphylaxis or pyrogen response. The composite hydrogel showed a good histological compatibility in the in-vivo study. The results indicated that the polyvinyl alcohol/collagen composite hydrogels have promising applications for pharmaceutical and biomedical fields.     

Synthesis and Comparison of Extraction Properties of p‐tert‐Butylcalix[n]arene Nitrile Derivatives for Selected Metals and Dichromate Anions

The article describes the syntheses and extraction properties of two p‐tert‐butylcalix[6]arene nitrile derivatives (3 and 4). The trinitrile derivative 3 has been synthesized from 5,11,17,23,29,35‐hexa‐tert‐butyl‐37,38,39,40,41,42‐hexahydroxycalix[6]arene 1. The compound 1 was directly converted to its hexanitrile derivative 4. In these syntheses, it was thought to explore the role of nitrile sites in the extraction of various metal cations and HCr₂O₇ ^?/Cr₂O₇ ^2? anions. The liquid‐liquid extraction properties of 3 and 4 towards selected alkali/transition metal cations and HCr₂O₇ ^?/Cr₂O₇ ^2? anions are reported. It has been observed that receptor 3 does not extract alkali/transition metal cations effectively, but shows affinity towards HCr₂O₇ ^?/Cr₂O₇ ^2? anions at low pH. The compound 4 is an effective form for transferring Ni²⁺ selectively, while it shows poor transferring ability for HCr₂O₇ ^?/Cr₂O₇ ^2? anions from an aqueous into a dichloromethane layer. It was observed that the cavity size of the calix[n]arenes and the cooperativity of the functionalities play important roles in two phase extraction systems.     

ToxML,a data exchange standard with content controlled vocabulary used to build better (Q)SAR models

Development of accurate quantitative structure–activity relationship (QSAR) models requires the availability of high quality validated data. International regulations such as REACH in Europe will now accept (Q)SAR-based evaluations for risk assessment. The number of toxicity datasets available for those wishing to share knowledge, or to use for data mining and modelling, is continually expanding. The challenge is the current use of a multitude of different data formats. The issues of comparing or combining disparate data apply both to public and proprietary sources. The ToxML project addresses the need for a common data exchange standard that allows the representation and communication of these data in a well-structured electronic format. It is an open standard based on Extensible Markup Language (XML). Supporting information for overall toxicity endpoint data can be included within ToxML files. This makes it possible to assess the quality and detail of the data used in a model. The data file model allows the aggregation of experimental data to the compound level in the detail needed to support (Q)SAR work. The standard is published on a website together with tools to view, edit and download it.     

Qsar Models for Predicting the Acute Toxicity of Selected Organic Chemicals with Diverse Structures to Aquatic Non-Vertebrates and Humans

Abstract

The linear and non-linear relationships of acute toxicity (as determined on five aquatic non-vertebrates and humans) to molecular structure have been investigated on 38 structurally-diverse chemicals. The compounds selected are the organic chemicals from the 50 priority chemicals prescribed by the Multicentre Evaluation of In Vitro Cytotoxicity (MEIC) programme. The models used for the evaluations are the best combination of physico-chemical properties that could be obtained so far for each organism, using the partial least squares projection to latent structures (PLS) regression method and backpropagated neural networks (BPN). Non-linear models, whether derived from PLS regression or backpropagated neural networks, appear to be better than linear models for describing the relationship between acute toxicity and molecular structure. BPN models, in turn, outperform non-linear models obtained from PLS regression. The predictive power of BPN models for the crustacean test species are better than the model for humans (based on human lethal concentration). The physico-chemical properties found to be important to predict both human acute toxicity and the toxicity to aquatic non-vertebrates are the n?octanol water partition coefficient (Pow) and heat of formation (HF). Aside from the two former properties, the contribution of parameters that reflect size and electronic properties of the molecule to the model is also high, but the type of physico-chemical properties differs from one model to another. In all of the best BPN models, some of the principal component analysis (PCA) scores of the ¹³C-NMR spectrum, with electron withdrawing/accepting capacity (LUMO, HOMO and IP) are molecular size/volume (VDW or MS1) parameters are relevant. The chemical deviating from the QSAR models include non-pesticides as well as some of the pesticides tested. The latter type of chemical fits in a number of the QSAR models. Outliers for one species may be different from those of other test organisms.     

Experiences with the Application of QSAR in the Routine of the Notification Procedure

Abstract

On behalf of the Umweltbundesamt the Fraunhofer Gesellschaft has developed a software system (SAR-system) comprising more than 90 estimation models for endpoints relevant in environmental risk assessment. These estimation models are based on the approach of quantitative structure-activity relationships (QSAR). All models were checked for their validity and application range. In the last months the Umweltbundesamt started to test the applicability of some models concerning the endpoints fish acute toxicity, daphnia acute toxicity and ready (i.e., ultimate) biodegradability in the daily routine of the notification procedure. For testing these models the corresponding confidential data given in the dossiers of substances notified 1993 in Germany, were used. We were able to make calculations for 36% of the notified substances. For the remaining 64% of the chemicals it was impossible to accomplish SAR estimations due to several reasons, e.g., ionic structure of the compounds. Different results for the applicability of the mentioned endpoints are obtained. The predictions of the fish and Daphnia toxicity are in sufficient agreement with the experimental results, in case of the fish toxicity we receive 58% agreement, for the Daphnia toxicity 56% The corresponding values which were obtained in the US EPA/E.C. Joint Project on the evaluation of (quantitative) structure activity relationships were 82.3% and 70.9% About 300 different models were used for the calculations of these endpoints within the framework of the EPA/EC project. The SAR-system presented here contains 8 models for estimating the fish toxicity and 6 models for the Daphnia toxicity. For the prediction of the biodegradability the results obtained with the SAR-system are rather poor and have to be improved. Meanwhile the SAR-system is commercially available and can be ordered at the Fraunhofer Institute for Environmental Chemistry and Ecotoxicology, Schmallenberg (Germany).     

Integrated Access to Genomic and Other Bioinformation: An Essential Ingredient of the Drug Discovery Process

Abstract

Due to the high rate of data production and the need of researchers to have rapid access to new data, public databases have become the major medium through which genome mapping and sequencing data as well as macromolecular structural data are published. There are now more than 250 databases of biomolecular, structural, genetic, or phenotypic data, many of which are doubling in size annually. These databases, many of which were created and are maintained by experimentalists for their own research use, provide valuable collections of organized, validated data. However, the very number and diversity of databases now make efficient data resource discovery as important as effective data resource use. Existing autonomous biological databases contain related data which are more valuable when interconnected than when isolated. Political and scientific realities dictate that these databases will be built by different teams, in different locations, for different purposes, and using different data models and supporting DBMSs. As a consequence, connecting the related data they contain is not straightforward. Experience with existing biological databases indicates that it is possible to form useful queries across these databases, but that doing so usually requires expertise in the semantic structure of each source database. Advancing to the next level of integration among biological information resources poses significant technical and sociological challenges.     

Physicochemical and Graph Theoretical Descriptors in Developmental Toxicity SAR: A Comparative Study

Abstract

Chemical insults to the developing fetus can lead to growth retardation, malformation, death, and functional deficits. The present study seeks to determine if physicochemical and/or graph theoretical parameters can be used to determine a structure-activity relationship (SAR) for developmental toxicity, and if consistency is observed among the selected features. The biological data utilized consists of a diverse series of compounds evaluated within the Chernoff-Kavlock in vivo mouse assay. Physicochemical parameters calculated correspond to electronic, steric, and transport properties. Graph theoretical parameters calculated include the simple, valence, and kappa indices. Both sets of parameters were independently applied to derive SARs in order to compare the quality of the respective models. Multiple random sampling, without replacement, was utilized to obtain ten training/test partitions. Models were built by linear discriminant analysis, decision trees, and neural networks respectively. Comparisons on identical sets of data were carried out to determine if any of the model building procedures had a significant advantage in terms of predictive performance. Furthermore, comparison of the features selected within and across the model building processes led to the determination of model consistency. Our results indicate that consistent features related to developmental toxicity are observed and that both physicochemical and graph theoretical parameters have equal utility.     

QSAR-based toxicity classification and prediction for single and mixed aromatic compounds

Quantitative structure-activity relationships (QSARs) based on the octanol/water partition coefficient were employed to predict acute toxicities of 36 substituted aromatic compounds and their mixtures. In this study, the model developed by Verhaar et al. was modified and used to calculate octanol/water partition coefficients of chemical mixtures. To validate the model, acute toxicities of these chemicals were measured to Vibrio fischeri in terms of EC⁵⁰. The results indicated that the obtained QSAR models could be used to predict toxicities of samples consisting of these substituted aromatic compounds, individually or in combinations. The obtained equations were proved to be robust enough by using the leave-one-out test method. By classifying these chemicals into two groups, polar and non-polar, the toxicities of chemical mixtures within each group can be predicted accurately from their calculated partition coefficients.